Server Quality Checklist

Tool Scores

• mcp_vision_augment_clear_cacheA
  3.5/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  No annotations are provided, so the description carries full burden. It discloses the action (clears local result cache) and notes the TTL upper limit controlled by VISION_AUGMENT_CACHE_TTL_SECONDS, providing some context. However, it does not describe any side effects, permissions required, or the impact of clearing the cache.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single sentence that conveys the core purpose and an environmental constraint. It is succinct with no redundancy.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a simple cache-clearing tool with no parameters, the description is mostly adequate. It covers the action and a relevant configuration detail, but lacks usage context and any note about when this would be appropriate or how it interacts with the sibling tools.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The tool takes no parameters, and schema coverage is 100% with zero properties. The description does not need to explain parameters, and none are present accordingly.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's function: '清除本地结果缓存' (clear local result cache). It uses a specific verb and resource, but does not differentiate from sibling tools mcp_vision_augment_vision or mcp_vision_augment_health, which are distinctly different operations.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  No guidance is provided on when to use this tool or when not to. The description implies a cache-clearing operation but does not mention scenarios or alternatives.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• mcp_vision_augment_visionA
  4.2/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  With no annotations, the description carries the behavioral transparency burden. It discloses the unified return envelope, the fallback chain through OpenAI-compatible channels to local Ollama VL, and that OCR/document parsing run locally. This adds meaningful context beyond the schema, though it does not mention rate limits, timeouts, or error code specifics.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is two succinct sentences: the first states the tool's role, the second explains the envelope and fallback behavior. It front-loads the main purpose, uses the space efficiently, and avoids redundancy with the schema.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  The tool is complex (multiple task types, multiple backends), and the description covers the envelope, backend fallback, and local processing. The schema fully documents all parameters. However, there is no per-task description of what 'result' contains, and the VISION_AUGMENT_ALLOW_URLS requirement appears only in the schema, not the description. Given the complexity, these are minor gaps.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100%—every parameter (task, source, language, task_type) has a clear description in the input schema. The description adds no extra parameter-level semantics, so the baseline of 3 is appropriate. The description's mention of the return envelope is about output structure, not parameter meaning.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description gives a specific verb+resource: 'provides image viewing, OCR, and document parsing capabilities' for LLMs without vision. It clearly distinguishes itself from sibling tools (health, clear_cache) by enumerating the three task types (reasoning, ocr, document) and the unified JSON envelope.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description clearly implies when to use the tool (vision understanding, OCR, document parsing) via the task_type enum, and the fallback behavior indicates the intended scenarios. However, it does not explicitly state when not to use it or contrast with sibling tools, so it stops short of a full 5.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• mcp_vision_augment_healthA
  4.4/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  With no annotations provided, the description carries the full burden. It explicitly states that the tool excludes keys ('不含密钥'), which is an important behavioral trait regarding sensitive data. It also implies a read-only, non-destructive nature by calling it a probe/detection, but does not explicitly confirm side-effect-free behavior.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, concise sentence that front-loads the main purpose ('环境探测') and then elaborates on components and outputs. Every clause adds value without redundancy or unnecessary details.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's simplicity (no params, no output schema), the description covers essential aspects: what is checked, that keys are excluded, and the kind of feedback provided (missing configurations and install commands). It does not specify the exact output format, but this is a minor gap for a health check tool.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The tool has zero parameters and the schema is empty (100% coverage). Baseline for no parameters is 4; no additional parameter explanations are necessary since there are none to describe.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description uses a specific verb (检查/check) and concrete resources (视觉通道/Ollama/OCR/文档引擎), clearly indicating a health/environment probe. It distinguishes itself from siblings like mcp_vision_augment_vision (which likely performs vision tasks) and clear_cache (cache management) by focusing on configuration status.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides clear context for when to use the tool: to detect missing configurations and provide installation commands. However, it does not explicitly mention when not to use it or name alternative tools, so it stops short of full usage guidance with exclusions.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.